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Deep learning (DL) based semantic communication methods have been explored totransmit images efficiently in recent years. In this paper, we propose agenerative model based semantic communication to further improve the efficiencyof image transmission and protect private information. In particular, thetransmitter extracts the interpretable latent representation from the originalimage by a generative model exploiting the GAN inversion method. We also employa privacy filter and a knowledge base to erase private information and replaceit with natural features in the knowledge base. The simulation results indicatethat our proposed method achieves comparable quality of received images whilesignificantly reducing communication costs compared to the existing methods.

Generative Model Based Highly Efficient Semantic Communication Approach for Image Transmission